Abstract

The projection data measured in computed tomography (CT) and, consequently, the slices reconstructed from these data are noisy. For a reliable diagnosis and subsequent image processing, like segmentation, the ratio between relevant tissue contrasts and the noise amplitude must be sufficiently large. By separate reconstruction from even and odd numbered projections, two images can be computed, which only differ with respect to noise. We show that these images allow an orientation and position adaptive noise estimation for level-dependent threshold determination in the wavelet domain.